Application Guide

How to Apply for AI Engineer, Marketing

at Planet

🏢 About Planet

Planet uniquely combines space technology with data analytics, operating the world's largest constellation of imaging satellites to provide Earth observation data for commercial, environmental, and humanitarian purposes. As both a space company and data company, they offer the rare opportunity to work with massive satellite datasets while contributing to meaningful global challenges like climate monitoring and disaster response.

About This Role

This AI Engineer role focuses specifically on applying artificial intelligence within Planet's marketing organization to improve efficiency, scalability, and performance. You'll be defining AI strategies, architecting solutions, and implementing projects that leverage Planet's unique satellite data to enhance marketing operations and customer engagement.

💡 A Day in the Life

A typical day might involve collaborating with marketing teams to identify AI opportunities, developing models to analyze customer engagement patterns, processing satellite data pipelines to extract marketing insights, and presenting findings to cross-functional stakeholders. You'd balance technical implementation with strategic planning to ensure AI solutions align with both marketing goals and Planet's mission-driven culture.

🎯 Who Planet Is Looking For

  • Experience implementing AI/ML solutions in marketing contexts (lead scoring, customer segmentation, content optimization)
  • Technical proficiency with cloud platforms (AWS, GCP, or Azure) and big data tools for processing satellite imagery datasets
  • Understanding of both marketing metrics/KPIs and AI model evaluation metrics to demonstrate business impact
  • Ability to translate between technical AI concepts and marketing team needs in a remote, collaborative environment

📝 Tips for Applying to Planet

1

Highlight specific experience with geospatial data or satellite imagery in your resume, even if from academic projects

2

Demonstrate how you've used AI to solve marketing problems with concrete metrics (e.g., 'improved lead qualification accuracy by X%')

3

Research and reference specific Planet products or datasets (like PlanetScope or SkySat) in your application materials

4

Show remote collaboration experience, particularly in cross-functional teams between technical and non-technical stakeholders

5

Connect your AI experience to Planet's mission by suggesting how AI could enhance their marketing of Earth observation data

✉️ What to Emphasize in Your Cover Letter

['Your experience bridging AI/ML and marketing functions with specific examples', "How you've worked with large datasets (especially if geospatial or imagery-related)", "Understanding of Planet's dual identity as both space technology and data company", 'Remote collaboration experience and ability to work across time zones']

Generate Cover Letter →

🔍 Research Before Applying

To stand out, make sure you've researched:

  • Planet's specific satellite constellations and data products (PlanetScope, SkySat, RapidEye)
  • Recent Planet customer case studies in commercial, environmental, or humanitarian sectors
  • Planet's marketing content and channels to understand their current approach
  • The company's distributed/remote work culture and global office locations

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 How would you approach applying AI to marketing a highly technical product like satellite imagery data?
2 Describe a time you implemented an AI solution that improved marketing efficiency or scalability
3 What challenges specific to satellite imagery data would affect AI model development for marketing use cases?
4 How do you measure the success of AI projects in marketing contexts?
5 How would you collaborate with non-technical marketing team members in a remote setting?
Practice Interview Questions →

⚠️ Common Mistakes to Avoid

  • Generic AI experience without connection to marketing applications or business impact
  • No examples of working with large datasets or cloud platforms
  • Failing to demonstrate understanding of Planet's unique space+data business model

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Planet!